NumXL Support Desk

Appendix E: Hannan-Quinn Information Criterion (HQC)

The Hannan-Quinn information criterion (HQC) is a measure of the goodness of fit of a statistical model, and is often used as a criterion for model selection among a finite set of models. It is not based on log-likelihood function (LLF), and but related to Akaike's information criterion.

Similar to AIC, the HQC introduces a penalty term for the number of parameters in the model, but the penalty is larger than one in the AIC.